Ifpschool2016

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PSM Which mobility for the future ?

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Ifpschool2016

  1. 1. gabriel.plassat @ ademe.fr http://gabrielplassat.fr Mobility & Transportation System for the Future Which Mobility for the future ? For every one, everywhere In a world of less raw material and more intelligence …
  2. 2. gabriel.plassat @ ademe.fr Agence De l’Environnement et de la Maîtrise de l’Energie Service Transports et Mobilité, en charge des Energies et de la Prospective Mobility ? Business Models Multi modality Real time Pollutions Industry GHG Commuter (Open) Data SmartPhone Physical meeting VEHICLE ENERGY Infrastructure Future of Work
  3. 3. http://transportsdufutur.typepad.fr
  4. 4. Horse > Car > ?
  5. 5. LIEN =>
  6. 6. Vincent Besson : Change ahead will be as violent as the transition from horse to the automobile » Michel Serres : Digital evolution, 3rd of our species after writing and printing Stéphane Vial : « After the wood , wind, water, coal and steel , and thermal and electrical machines , digital is the new matrix ».
  7. 7. Innovation What’s an innovation ? Who can innovate ?
  8. 8. • The digital becomes the dominant technique. New Industrial empires are built around • The mutation of the object in the service is a chance • A new ecosystem is created , users are at the center , the data is the fuel ( renewable) • Innovations are carried by start-ups
  9. 9. Money : more GDP => more km, more speed, alone … moins de TC : 0 100 200 300 400 500 600 700 800 900 0 10 20 30 40 50 Per Capita GDP @ PPP VehiclesPer1000People 0 100 200 300 400 500 600 700 800 900 0 10 20 30 40 50 Per Capita GDP @ PPP VehiclesPer1000People Vehicle Density vs. Income (for 2002 and 2007) Singapore Hong Kong United States W. Europe & Japan Empreinte écologique, Écart en % / moy (UK) Fundamentals of Mobility
  10. 10. http://air-climate.eionet.europa.eu/docs/ETCACC_TP_2009_10_prelim_AQQanalysis_2008.pdf First SYMPTOMS : Air POLLUTION Cadastre population POPULATION EXPOSITION POLLUTION IMPACT Function DESEASE & DEAD Numbers 0 EXTERNAL COSTS Air Pollution Map Population repartition COSTS [ ]
  11. 11. Example : Impact of technology on NO2 emissions and health A series of technical and scientific skills very different Some experts in this sequence: for example ANSES g / s of pollutant (eg NO2): vehicle exhaust depending on : - technology (manufacturer, Euro) - use of the vehicle (speed, accel., T °) - maintenance, aging gNO2/m3: concentration in the atmosphere depending on : - the atmospheric chemistry and pollutants already there! - the weather (temperature, wind) - the vehicle fleet (g / s) and use (nb veh, km) - other NO2 Health impact, based on dose / response: variable depending on the mixtures difficult to know the impact of a single component Link vehicle exhaust, concentration, air pollution, health response … => Strong uncertainties Air Quality & Pollutants Emissions Cadastre population POPULATION EXPOSITION POLLUTION IMPACT Function DESEASE & DEAD Numbers 0 EXTERNAL COSTS Air Pollution Map Population repartition COSTS [ ]
  12. 12. Need for a method and tools to choose Need tools to select, adapt / user / criteria: •Tool to create and / or access to new strategic data, •Multi criteria aggregation tool: pollutant, CO2, €, ... •Tool for comparison and selection Some examples ...
  13. 13. comparaison des filières PL 19T Mesures et Estimations(*) 0 0.05 0.1 0.15 0.2 0.25 0.3 0.35 0.4 0.45 0 1 2 3 4 5 6 NOx (g/km) Particules(g/km) 60 km/h 903 500 763 900(*) 710(*) 20 km/h 20 km/h 20 km/h 60 km/h 60 km/h 60 km/h 60 km/h 20 km/h 20 km/h Diester Emulsion Diesel GNV sans FAP avec FAP avec FAP/DeNOx 1ère monte (neuf) 20 km/h 9401345 730(*) EFFET du FAP EFFET de l'usage 630 615* 875* 60 km/h EFFET DeNOx 1435 20 km/h Heavy Duty Vehicle (19 tons) : Pollutants and GHG Particles(g/km) Speed Effect DPF Effect DeNOx Effect
  14. 14. How to aggregate pollutants, GHG, energy, costs, noise … ? gNOx/km => €NOx /km gCO2/km => €CO2 /km dB/km => €dB /km … Economy => € /km 3  Vehicle lifetime € CO, HC, NOx, PM, GHG, dB, Economy Cadastre population POPULATION EXPOSITION POLLUTION IMPACT Function DESEASE & DEAD Numbers 0 EXTERNAL COSTS Air Pollution Map Population repartition COSTS [ ] DieselNGVLPG Costs for pollutants in € / ton CO HC NM NOx Particles CO2, CH4 0 2000 7700 126 900 40 Pollutants and GHG : aggregation by Euros
  15. 15. 0 0.02 0.04 0.06 0.08 0.1 0.12 0.14 0.16 D iesel D iester30 ém ulsion FAP FAP+D eN O X G N V D iesel D iester30 ém ulsion FAP FAP+D eN O X G N V coût GES carburant coût GES véhicule coût Part. coût Nox Vitesse moyenne 20 km/h Vitesse moyenne 60 km/h Coût externe en euro/km Heavy Duty Vehicle (19 tons) : Pollutants + GHG External costs in euro/km Average speed 60 km/h Average speed 20 km/h Fuel GHG cost Vehicle GHG cost Particle cost NOx cost
  16. 16. 0 500 1000 1500 2000 2500 3000 3500 0 50 100 150 200 250 300 CO2 Véhicule (fossile et renouvelable) g/km => BONUS / MALUS Coût puits à la roue (euros) CO2 fossile et polluants sur 200 000 km GNV Essence Diesel FAP Diesel sans FAP VUL E85 C3 HDi sans FAP Effet NOx !! Cycle NEDC : 118 gCO2 / 1707 € Cycle réel : 129 gCO2 / 2813 € Trail 125 Scooter 125- 400 250- 600 Sport 900 2 roues cycle réel 200 000 km (rajouter prod.) External costs for Car and 2 wheels : Pollutants + GHG GHG vehicle (fossil + biofuell) g/km GHG + Pollutants costs vehicle (fossil + biofuell) Over 200.000 km in €/km C3 HDi w/o DPF NOx effect NEDC cycle : 118 gCO2 / 1707 € Real cycle : 129 gCO2 / 2813 € 2 wheels real cycle 200 000 km
  17. 17. Suivi conso permanent en fonction de l’exploitation Suivi permanent des émissions de tous les polluants gazeux et particules en fonction de l’exploitation What IF real pollution was known in real time ? Who will produce this Information ?
  18. 18. Constraint on pollutants => Emissions norms Euro (IV to VI) Links pollutants / fuel consumption and GHG Le transport du futur devra concilier les 3 aspects : Diversification (alternative to fossile) + GHG emissions under constraints (Factor 4) + Pollutants Emissions under constraint (Euro X) => Optimisation of « components » like vehicle is not sufficient => Need to optimise also the SYSTEM Constraints on energy & GHG => diversification and efficiency Addition of constraints
  19. 19. Shanghai, China
  20. 20. Baku, Azerbaijan
  21. 21. The finding is the result elements studied today separately, in silos. While locks & solutions are mainly in the interstices. We are looking for solutions in each "silo" where we used to look ... « You looking for your key during the night under lamp, simply because you can see … »
  22. 22. Transports & Mobility, Today More info, clic here NEW Veh All Veh 1 to 3 Millions Drivers out of Norm : -insurance, -Permit -Technical control years
  23. 23. More info, clic here Transports & Mobility, Today urban Peri-urban, rural Mtoe Mtoe40 Mtoe road 50Mtoe tGHG/y
  24. 24. essential parameters : Type of mobility, daily – occasional, constraint - leisure, ... Age, income, Place of residence, Alternative offers available Identification and understanding of practices, of daily activities The solutions must adapt to the multiplicity of situations (explosions configurations) be "as good" as the individual car possessed: - economy, - flexibility, - environment - quality service ... Which mobility? Socio profil Mobility Behavior Automotive Behavior
  25. 25. Which mobility? PARIS Mobility Choice from Monday to Friday In PARIS, multimodality – on average in France, still the car
  26. 26. Which mobility? Why do you use less your personnal car ? Reduce my demand It’s not green Lose my time stress It’s not usefull It’s expensive First reason to reduce car utilisation is economic (selfish) then green (altruistic)
  27. 27. Which mobility? First reduction concern « non constraint » travel Utilisation ratio of personal car Home - Job Professional Trip Shopping Leisures
  28. 28. Again, First reason to use bicycle is economic & healthy (selfish) then green (altruistic) Why do you use more a bicycle ? Increase demand It’s green It’s economic It’s healthy It’s rapid No stress Which mobility?
  29. 29. Under constraints : €, time/congestion, health, confort, connectivity, … , GHG and pollution 1. Reduction of a unique solution owned (car) 2. Behavior modifications : Selfish AND Altruistic 3. Now We start to THINK before taking a car : 1. other mode ? 2. Share with other, share trip 3. Adapt my driving style But CONSTRAINTS WILL INCREASE … MODIFICATIONS WILL NOT BE SUFFICIENT IMPROVE OUR COMMON KNOWLEDGE : HOW PEOPLE ARE MOVING ? Which mobility - Summary
  30. 30. Which route toward Factor 4 ? New Technology New Vehicle on the road : • €, • too slow ! • If less FC then more km ! TODAY NO CLEAR and SHARED VISIONS TO REACH F4, Air Quality, reduce congestions GHG, Air Quality AQ
  31. 31. 4 pillars to consider a Mobility System The meeting, in a given area, of a user and … an energy: fossil, biomass, muscle, available through a distribution network, a vehicle (which converts the energy in motion): truck, car, bicycle, walking, available in own account or for others, property or shares, an infrastructure (which allow the movement and possibly easier): road, rail, urban planning, but also interfaces to change 'vehicle' : station, parking, delivery area, logistics platform, and Information (which allowed yesterday to facilitate the movement, and who will, tomorrow, optimize it): theoretical hourly, hourly real-time traffic, weather, … A Mobility System allows In order to realise an activity. REMEMBER
  32. 32. Industry Time scale for innovation Linked with Actors Vehicle : Automotive, HDV, 2 wheels, bicycle 5-10 years Infrastructures : shared, constraints private Energy : Oil, energy, some cities (biogas), some farmers (biofuels) 10-20 years Infrastructures : network distribution private Infrastructure : road, parking, rail operator, 20-50 years Vehicles, energy, information Publics Informations : Telecoms, citizen (!) 0.5-2 years Vehicle, energy, infra Publics (source) and private 4 pillars to consider a Mobility System
  33. 33. What performance criteria for a solution Mobility and Transport • Time door to door • Cost: investment, km • Quality: robustness to uncertainties, always-on connectivity or zero noise • Security: perceived real • Environmental performance: known or unknown, knowledge generally leads to optimization. The fact that they are known is already a step forward: • pollutants, GHG • Energy diversification, • Waste direct and indirect • noise • urban land use • link health / mobility (soft modes, pollution cabin)
  34. 34. • Environment, • Security, • Congestion, • Energy (unique) (Europ 14 M) Mobility 1.0 Mobility System Optimisation is not anymore an option
  35. 35. 4 more free time in 100 years 0 100 200 300 400 500 600 700 aujourd'hui début siècle Time Transport Budget : Stable ~ 1h for over 20 years Need more speed for more distance Milliers d’heure The fundamentals, time TODAY 1900
  36. 36. From ultra deep exploration To ultra deep conversion Is fuel expensive ? 1.5€ (0.5€ for oil company) for 42 MJ Oil and fuels High Technology, More and more risky, High characteristics (energetic density in volum) Without any public recognition At a very LOW PRICE !!
  37. 37. The oil, squeezed between economic / environmental, toward a transition: variable depending on modes of transport, an acceptable price with alternatives necessarily massive to have a impact, in two waves: 1. explosion in the number of pathways, 2. specialization. 1st Wave: • 1st and 2nd generation biofuels with difficult assessments • Natural Gas "additived" with Biogas and H2, • Electricity (s) with variable performances, • Short loop (HAU, biogas, crude oil) in public or private management, With multiple solutions in most cases: actual performance of the multi well to wheel (Biocarb, electricity) sensitive Difficult Political decision making, little investment in infrastructure, difficult for manufacturers to follow all the pathway => The first wave could be long ... The fundamentals, Energy
  38. 38. 4000 engines / day Millisecond, milligram, Cubic Millimeter of fuel Micron machined 120 000 parts identical but all different 5 years warranty – 100 000 km Full Energy in 3 minutes 20+/- 0.5°C Very low emissions and consumption / kWh Vehicle – Internal Combustion Engine Particules NOx HC CO EURO III EURO 0 EURO -1 EURO I EURO II EURO IV 18 14,4 11,2 14 2,4 3,50,36 0,15 1,10,10 5,0 3,5 8,0 7,0 0,02 0,660,46 4,5 4,0 2,1 1,5 EURO V2,0 Understand domination (2)
  39. 39. time Fuel Consumption Reduction due to Technical progress But real progress are null : Accessories (€ benefits) Pseudo performance (€ benefits) Constraints emissions / safety. 60 years of difference and same FC … Progress, but for whom? The fundamental, car economic model
  40. 40. 50 70 90 110 130 150 170 190 0 5000 10000 15000 20000 25000 30000 35000 40000 PSA BMW TOYOTA Puiss(kW) Prix (€) E E E ET D E D D D D D D D E E D Power (maxi) Is easy to sell ! 1200 1250 1300 1350 1400 1450 1500 0 5000 10000 15000 20000 25000 30000 35000 40000 PSA BMW TOYOTA Prix (€) Masse(kg) The car is sold by kilo, no vehicle manufacturer sell a car lighter and more expensive D D D D D D E EE ET The fundamental, car economic model
  41. 41. time Fuelcons Potentiel of Technical benefits Marketing mass Real progress From "new needs" of consumers : Comfort, safety, 4x4 Increase "pseudo-performance" YESTERDAY The fundamental •Power (max, so unused by the client ...) •Flat screens in the headrests, air conditioning multizone ... (mass Merchant) •Respecting standards (Euro, security) •While being 'similar' in use => energy efficiency is not easy to sell time Fuelcons Reduction in Marketing mass Isoperformance => "90g Now" no extra cost More Marketing Mass More technology "My minivan hybrid" TOMORROW ou The fundamental, car economic model
  42. 42. Mobility Immobility Activity MutationS
  43. 43. Where are you working ? In US, 30% of workers are « alone » and it’s increasing
  44. 44. In the same time…
  45. 45. In the same time…
  46. 46. In the same time… VIDEO Google History
  47. 47. What about Health and Mobility ?
  48. 48. In the same time…
  49. 49. In the same time…
  50. 50. How to join the « power of network » @BlaBlaCar_FR
  51. 51. Question is not « How can we can a 2 l/100 km car ? » But « What are the best mobility experiences, Who will produce theses experiences ? » Multimodality, Connexion, Mobility … Digital become Major Technology We see the world across Digital technology Automotive is not main Matrix anymore A RETENIR
  52. 52. Fashion clothing « low cost & functional»2-3 wheels … From multi-use… Std Business model Fashion vehicle Cybercar High technology Transition from multi- to mono-use increase efficiency, reduce congestion and Allow new energy and technology penetration like electricity … ( can answer to « why not yesterday ? Why tomorrow ? What’s gona change ? » ) Transition will appear with business model modification : from vehicle to mobility services To mono-use… Towards Mobility 2.0
  53. 53. Impact on objects? Options for Mobility 2.0 An efficient vehicle, light can more easily be integrated into services: because the operator has an interest (TCO) because the user does not buy the car! We will use vehicles that we will not want to buy! REMEMBER REMEMBER: New mobility system change behavior and affects vehicle’s specification, and therefore the technologies to implement ... New competitors are coming!
  54. 54. Mono usage 2-3 roues … From multi-use… Fashion clothing Walk, Bike Vélib’ Car Car sharing Location Autolib’ Carpooling Taxi Transp. On demand Bus, tram métro taxi Individual association business collective Public Semi public Private
  55. 55. All energies B to C et B to B Functionnality economy Top down Bottom up B to B Real Perfo Emissions Real Fuel cons TCO Mobility 2.0 Complete mobility service from door to door Oil + engine Multi-usage Economy of vehicle Top down B to C & B to B Mobility 1.0 + Infra 2.0 + New Authority 2.0 (multimodal, With targets Air Quality, GHG, congestion…) + Personnal Travel Assistant + Open Data (etalab) Political Decisions REMEMBER
  56. 56. One example of Mobility 2.0 system
  57. 57. Autopartag e entre part. Autop. « opéré » Flotte de voiture « opérée » Vélo Libre serv. Voiture possédée Integration / complexification for operators Integration / Simplification For users
  58. 58. Multimodality Source : EPFL, CERTU
  59. 59. Mobility Integrated & factor 4 More info, clic here How to engage these changement quickly ? Better utilisa° Of public transp.
  60. 60. From horse to car From car to ?
  61. 61. What if we would have 2 person in a car (average) ? More info, clic here -40 % on GHG, pollu°, conso (-10% long.dist -10% urbain -20% rural) sur VP-France -20 % on GHG, pollu°, conso NRJ sur Secteur Transport -5 % GHG France -8 Mtoe/year (sur 160) - 8 Md€/year (oil cost) France More than half electric Consumption of all Buildings in France (13 Mtep) 20 years of techno. Reduction benefit (2% reduction / year) Techno VP - France 40 to 60 years for same Result on all vehicle Techno VP - France Increase PT by factor Y France Close X nuclear reactors Out of 58 France AND IF …
  62. 62. Integration & Simplification of all transports modes More info, clic here A.P.M. Personal Travel Assistant (PTA) Autolib Vélib CarSharingPeer2 Peer CarPooling YesterdayToday Tomorrow Public = private Indiv = Collective => « free seat market » Simple & real time access (insurance, inscrip°…) Simple & real time exit (payment, reputa°)
  63. 63. With the service we can (need) to Re-design the vehicle : EDAG & Vélib … Velib is an innovation, but a system innovation bring with ITS, infrastructure and business model Velib bicycle is not a good bicycle but Velib service is successfull ! Velib service bring new Practise. « Bad » Velib bike design are low important than benefits on Velib service. Then Vehicle designed for services will be « poor » for standard vehicle consumer & GE will be best positionned to design EV for Mobility Services …
  64. 64. Always Car but BETTER utilisation & connected to Public Transport More info, clic here New Car and other Nrj Lighter Pay as you move More passenger per car Raw material & Investment In excess Raw material & Investment mutualised Pay as you use Access simplif. Payment Insurance Identity confidence Identity Historic reputation
  65. 65. + Network Tool for simplification
  66. 66. par @15marches, Stéphane Schultz
  67. 67. « Company Value in Digital economy : its capacity to capture positive externality created by the users »
  68. 68. LIEN => LIEN =>
  69. 69. Open source vs Patents TESLA , TOYOTA Hydrogen
  70. 70. « Data is the new oil » : user irruption, knowledge access (but who will have the data ?)
  71. 71. How are we moving ? v1.0 (publ.)
  72. 72. How are we moving ? v2.0 (private)
  73. 73. Application Digital routes … « Bikability » How are we moving ? v2.0 (publ/private)
  74. 74. = Lot 2 Lot 3 Lot 4 How are we moving ? v2.0 (publ/private)
  75. 75. + = Lot 6 Pilotage + €€ Lot 5 How are we moving ? v2.0 (publ/private)
  76. 76. … by co-conception and experimentation Behavior CHANGE
  77. 77. TO Start, 3 wrong ideas… • IF we provide clear demonstration, people change • WRONG ! WE ARE NOT RATIONAL ! Even with benefits, people don’t change for clear reasons • Emotional, Cultural, Social parameters are involved in our decision process. We Are Rational
  78. 78. • People are always afraid to do new things, they like repetition … • WRONG ! Fear to change doesn’t exist. They are difference of culture, of understanding between people who design the solution and those who use them. • We change every day during our life. WE don’t like change
  79. 79. • We need constraint and obligation to change • WRONG ! If we put constraint and obligation, then we develop resistance and by pass. • A volontary basis change is important to keep it during time. Only constraint is efficient
  80. 80. People need to build its own way to change taking into account its day to day life We need to participate in the process of conception in order to provide its own rationality People need to be volontar in this process … In SUMMARY:
  81. 81. Deep Day to Day Analysis of the Activity • By description of the activity WE take a distance • We can SHARE this experience with our PEER • WE AGREE on a COMMON TARGET TARGET CO-BUILDING • We IDENTIFY changement possibilities • We DESIGN one solution • We AGREE to test it in certain conditions EXPERIMENTATION • WE TEST as soon as possible in real life • WE SHARE Feed back, LEARN and IMPROVE • WE CREATE experience and learning curves HOW to DO this ? Décembre 2014
  82. 82. 3 barriers for Integra° & Simplifica° More info, clic here Identify & Synchronise Main competences Industry Behavior Skill acceptability City
  83. 83. Toward Gov 2.0 More info, clic here constraints rewards €, time, … Knowledge database forecast
  84. 84. Example Ha:Mo by Toyota VIDEO HA:Mo
  85. 85. Multimodal Integration
  86. 86. Vehicle Evolutions bring by Behavior evolution Less is more … More info, clic here Car owned Car non-owned less km More pass/veh Car non-owned And operated less km More pass/veh More efficient
  87. 87. Integration & Simplification – DOUBLE Benefit ! More info, clic here Service Mobility brings : •Non-owned car •With New specifications •Used by citizens but not owned •Shared & operated •Using other energy •And much more efficient
  88. 88. It’s a system of computer working as a network (on wheels) V7.0 can activate Autopilot You see a car ?
  89. 89. IT’s a system of module in a vacuum tube created by a network of decentralised startups You see a new « train »
  90. 90. The major innovation will be not to own a car.. Smartphone, = new key
  91. 91. I
  92. 92. I
  93. 93. I
  94. 94. Driverless Cities
  95. 95. 106 Innovations are changing… Uber, Waze, Blablacar, Drivy… and next ? New mobility behaviour at large scale Massives solutions Techno & Socio Identify, support and accelerate 1er sector for GHG, pollution, congestion FabMob version proto FABRIQUE DES MOBILITES A NEW WAY TO SUPPORT INNOVATION
  96. 96. 107 MOOC Challenges et enjeux de la mobilité 2.0 • Startup definition : “temporary organization designed to search for a repeatable and scalable business model.” Innovation(s)
  97. 97. Open a large Sand Box For testing / learning And design future of mobility With the digital culture
  98. 98. 109 BRINGING RESOURCES TO ENTREPRENEURS
  99. 99. 110 Mise en réseau et animation des PARTENAIRES, PROJETS Utilisation et Production de COMMUNS Accès direct à des RESSOURCES Conseils, expertises ACCOMPAGNEMENT et Tutorats dans l’action REDUCE BARRIERS, SILOS, EXPLORE, CAPITALISE
  100. 100. 111 Les Partners bring resources to projects think tank écoles pôles
  101. 101. 112 Linving labs for testing (Infrastructures, vehicles, data, community, …) Expertises, Mentors Test bench, Calculation tools, Fablabs Learning capacity And Commons TO BRING RESOURCES AND ACCELERATIONS TO PROJECTS
  102. 102. 113 ILS ACCÈDENT : - RESSOURCES - COMMUNS - ACCOMPAGNEMENT IMPROVE THE COMMONS 5 PUIS 10 À 100 PAR AN
  103. 103. 114 Les Communs Innover par des plateformes ouvertes http://communs.lafabriquedesmobilites.fr
  104. 104. Research actions for Mobility 2.0 • Multi-field : socio to techno, ITS to logistic … • Users science : how generate confidance ? How to integrate new user behavior ? • Understanding & Optimisation of complex system, • New method to understand new demand, to design solutions with users and providers, • Tool for capitalisation in order to « industrialise » methodology (not the solutions) • Living labs, requested to test, design, validate
  105. 105. • Transition from Vehicle-object to Service is a chance for industry, citizen and environment, • New Value Chains, new actor, • Who will be multimodal mobility operator? • New ecosystem, user will be center • Data is the heart : to share • New culture to develop : education, learning in projects REMEMBER
  106. 106. REMEMBER At short term integration / simplification allow : • to do more w/o investment, • to increase resilience and possibilities, • to access to F4 road including QA, access equity But develop new risks : • ITS dependance, • Competence Transfert toward private entity (smart city) • Question of private data • Who & How will be manage constraints/rewards ? Complexus • Increase for all stakeholders : knowledge, skills, links • Synchronise all • Co-design mobility solutions beginning with real need of citizens activities More info, clic here
  107. 107. pers.km (flux) Billions City Extra urban Long dist. TOTAL PC PC serv. Train Bus Bike 2 W 2 W serv TOTAL 700 City Extra urban Long dist. TOTAL PC PC serv. Train Bus Bike 2 W 2 W serv TOTAL / pers / vehicle = City Extra urban Long dist. TOTAL PC PC serv. Train Bus Bike 2 W 2 W serv TOTAL vehicle.km combustion combustion + electricity electricity gCO2/km – MJ/km combustion combustion + electricity electricity Utilisation (% distance) average gCO2/km – MJ/km X = X = MTCO2 – MJ By energy By vehicle ADEME 2030-2050 calculations (GHG/MJ)
  108. 108. ADEME 2030-2050 calculations (GHG/MJ) 200,0 300,0 400,0 500,0 600,0 700,0 800,0 900,0 2005 2010 2015 2020 2025 2030 2035 2040 2045 2050 2055 Voyageurs March Voiture VUL Camion 325 Flux de véhicule (Md véh.km) Flux de voyageur (Md voy.km) et de Marchandises (G T.km) 343 377 711 790 750 425 428 300 77 85 60 24 22 27 pers.km, vehicle.km and ton.km(flux) Pers/veh in PC serv: 1,2 1,5 2 % flux by PC serv 0 (city/extra/LD) 10-10-5 25-20-15 Pers/veh in Bus ref +20% +20%/2030 % flux by Bike 4-1-0 10-6-0 15-7-0 % flux by Bus 6 10 15
  109. 109. ADEME 2030-2050 calculations (GHG/MJ) Emissions de GES en MTCO2 et facteur de réduction (réf 1990) 0,0 0,5 1,0 1,5 2,0 2,5 3,0 3,5 4,0 4,5 2005 2010 2015 2020 2025 2030 2035 2040 2045 2050 2055 71,2 17,7 32,1 40,6 21,9 10,1 14,5 11 3,5 121 72 29 Voyageurs VUL March 0,00 5,00 10,00 15,00 20,00 25,00 30,00 35,00 40,00 45,00 2005 2010 2015 2020 2025 2030 2035 2040 2045 2050 2055 Voyageurs VUL March 38,5 1 24,5 2 12 5 CONSOMMATIONS ENERGETIQUES en MTEP (liquide/gaz et électricité) Liquide/Gaz Liquide/Gaz Liquide/Gaz Electricité Electricité Electricité GHG emission (MTCO2) and reduction factor ENERGY in MTEP • « standard » Progress • Electric, plug-in : first for PC serv • 2030 mix fleet : 100 gCO2/km 25 millions PC : 5% EV, 9% plug-in • 2050 mix fleet : 56 gCO2/km 16 millions PC : 28% EV, 38% plug-in Biofuel potential : • 5 MTEP biogas • 3 MTEP liquid (2G)

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